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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Critical review and analysis of hydrogen safety data collection tools

The wider adoption of hydrogen in multiple sectors of the economy requires that safety and risk issues be rigorously investigated. Quantitative Risk Assessment (QRA) is an important tool for enabling safe deployment of hydrogen fueling stations and is increasingly embedded in the permitting process. QRA requires reliability data, and currently hydrogen QRA is limited by the lack of hydrogen specific reliability data, thereby hindering the development of necessary safety codes and standards [1]. Four tools have been identified that collect hydrogen system safety data: H2Tools Lessons Learned, Hydrogen Incidents and Accidents Database (HIAD), National Renewable Energy Lab's (NREL) Composite Data Products (CDPs), and the Center for Hydrogen Safety (CHS) Equipment and Component Failure Rate Data Submission Form. This work critically reviews and analyzes these tools for their quality and usability in QRA. It is determined that these tools lay a good foundation, however, the data collected by these tools needs improvement for use in QRA. Areas in which these tools can be improved are highlighted, and can be used to develop a path towards adequate reliability data collection for hydrogen systems.

08 HYDROGEN↗
DOE OSTI2025

Operating Klystrons at the Spallation Neutron Source – Two Decades of Perspective

Klystron amplifiers have been operated at the Spallation Neutron Source (SNS) in support of the user program since 2006. SNS tubes have amassed over 100,000 hours of high-voltage and filament-on time providing a significant source of operational statistics for high power, high-duty klystrons. Additionally, the SNS Radiofrequency (RF) Systems Group has developed operational methods to mitigate specific reliability challenges, such as cathode arcing and output power instability. Despite much progress, many of these challenges persist, prompting the SNS to update the procedures used for klystron processing as well as develop a higher throughput test stand.

Moss, John [ORNL] (ORCID:0009000085988916)↗
DOE OSTI2024

Best Practices Handbook for the Collection and Use of Solar Resource Data for Solar Energy Applications: Fourth Edition

As the world increasingly seeks low-carbon energy solutions, solar power emerges as the most abundant resource on our planet. However, the challenge of effectively harnessing this energy is crucial in the coming years. Solar energy applications such as photovoltaics, solar heating and cooling, and concentrating solar power use different technologies to capitalize on sunlight. Each system has unique capabilities and requirements, underscoring the need for reliable information about solar resources across diverse installations, from residential rooftops to large-scale power plants. This is especially important for substantial projects, often exceeding $1 billion in construction costs. Before embarking on such ventures, it is imperative to obtain accurate data concerning solar resource quality and reliability at specific sites. Developers require detailed historical information, including seasonal, daily, hourly, and, ideally, subhourly variability to effectively predict a power plant's annual performance. Without these vital data, financial analyses fall short. Moreover, with the growing adoption of distributed photovoltaics, integrating these generation sources becomes critical to maintaining grid reliability and stability. By accurately forecasting generation patterns, utilities and system operators can facilitate greater integration of solar energy, thus ensuring the operational stability of the grid. The complexity and importance of these issues have prompted the foremost experts in the field to collaborate under the auspices of the International Energy Agency's (IEA's) Photovoltaic Power Systems Programme (PVPS) Task 16 to publish this handbook, which summarizes state-of-the-art information about all these topics. The efforts focus on providing reliable data and insights that can help shape our investments in solar energy and drive a sustainable future.

14 SOLAR ENERGY↗
DOE OSTI2025

Neural correspondence to spectrum of environmental uncertainty in multiple-cue probability judgment system with time delay

Despite state-of-the-art technologies like artificial intelligence, human judgment is critically essential in cooperative systems, such as the multi-agent system (MAS), which collect information among agents based on multiple-cue judgment. Human agents can prevent impaired situational awareness of automated agents by confirming situations under environmental uncertainty. System error caused by uncertainty can result in an unreliable system environment, and this environment affects the human agent, resulting in non-optimal decision-making in MAS. Thus, it is necessary to know how human behavior is changed to capture system reliability under uncertainty. Another issue affecting MAS is time delay, which can delay agent information transfer, resulting in low performance and instability. However, it is difficult to find studies on the influence of time delay on human agents. This study is about understanding the human decision-making process under a specific system reliability environment by uncertainty with time delay. We used concepts of expected and unexpected uncertainty to implement reliability of the system usage environment with three types of time delay conditions: no time delay, regular time delay, and irregular time delay conditions. We used electroencephalogram (EEG) for human cognitive neural mechanisms in multiple-cue judgment systems to understand human decision-making. In the reliability of system usage environment, the unreliable system environment significantly creates less memory load by less utilization of system rules for decision-making. In terms of time delay, delayed information delivery does not significantly affect memory load for decision-making.

cognitive process↗
DOE OSTI2024

Bill Savings vs. Backup Power: Evaluating operational tradeoffs for home solar+storage systems [Slides]

This study explores tradeoffs between the use of home solar+storage systems for backup power versus day-to-day utility bill savings. The study focuses specifically on the “reserve setting” available with most home battery storage systems, which allow the customer to maintain some minimum level of storage in reserve in case of an unforeseen power interruption. The more capacity that is held in reserve, the greater the customer’s ability to ride-through possible power interruptions, but less capacity is then available to manage utility bills on a day-to-day basis. This study evaluates this operational tradeoff across a diverse set of locations and residential electricity tariff structures, relying on Berkeley Lab’s PRESTO model to stochastically simulate power interruption events, and exploring a range of sensitivities, including variations in customer value of lost load (VoLL), interruption frequency, and other key drivers. The results show that, in most circumstances, the opportunity cost of holding storage capacity in reserve, in terms of foregone bill saving, tends to outweigh any gains in reliability value associated with mitigated power interruptions. This finding is robust across tariff structures and across most of the sensitivities considered, including those related to rate level, customer load level, and storage sizing. There are a limited set of circumstances where raising the reserve setting improves the overall customer value (comprised of bill savings plus reliability value). Specifically, that exception occurs when all of the following conditions apply: (a) the customer resides in a location with exceptionally poor reliability, (b) the customer has exceptionally high VoLL; (c) the customer is on a net billing rate or on a TOU rate that allows grid discharging but not grid charging; and (d), depending on the location, the price arbitrage differential on that rate is relatively small. In all other circumstances analyzed, total customer value declines with reserve level.

14 SOLAR ENERGY↗
DOE OSTI2021

Predicting temperature-dependent ultimate strengths of body-centered-cubic (BCC) high-entropy alloys

This paper presents a bilinear log model, for predicting temperature-dependent ultimate strength of high-entropy alloys (HEAs) based on 21 HEA compositions. We consider the break temperature, T break , introduced in the model, an important parameter for design of materials with attractive high-temperature properties, one warranting inclusion in alloy specifications. For reliable operation, the operating temperature of alloys may need to stay below T break . We introduce a technique of global optimization, one enabling concurrent optimization of model parameters over low-temperature and high-temperature regimes. Furthermore, we suggest a general framework for joint optimization of alloy properties, capable of accounting for physics-based dependencies, and show how a special case can be formulated to address the identification of HEAs offering attractive ultimate strength. We advocate for the selection of an optimization technique suitable for the problem at hand and the data available, and for properly accounting for the underlying sources of variations.

36 MATERIALS SCIENCE↗
DOE OSTI2021

Bounding uncertainty in functional data: A case study

Functional data are fast becoming a preeminent source of information across a wide range of industries. A particularly challenging aspect of functional data is bounding uncertainty. In this unique case study, we present our attempts at creating bounding functions for selected applications at Sandia National Laboratories (SNL). The first attempt involved a simple extension of functional principal component analysis (fPCA) to incorporate covariates. Though this method was straightforward, the extension was plagued by poor coverage accuracy for the bounding curve. This led to a second attempt utilizing elastic methodology which yielded more accurate coverage at the cost of more complexity.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

OPET Hardware (Open PV Electrical Tool Hardware) [SWR-25-42]

OPET (Open-source Photovoltaic Electrical Tool) is used for performance measurements of solar photovoltaic (PV) devices in the field under natural sunlight or in the lab under artificial light. Its primary use is in research and development of solar cells and modules, specifically in reliability and durability research of PV devices. Some features and functions include: -IV curve measurements with linear or cosine distributed measurement points -PV device active loading at open circuit voltage (Voc), short circuit current (Isc) and maximum power point (Pmp) -Bias power supply to overcome series resistance in contact wires for Isc measurements and loading -PV voltage input in five ranges from 1V to 100V -PV current input ranges -Low current version, six current ranges from 1.1mA to 340mA -High current version, six current ranges from 50mA to 15A -IO ports for I2C and SPI temperature sensor Arduino extension boards -Integrated fan control This repository contains everything relating to the hardware of the OPET device. If you are looking for the firmware or software repositories, links are below: https://github.com/NREL/opet-firmware https://github.com/NREL/opet-control

McDanold, Byron [National Renewable Energy Laborat↗
DOE OSTI2024

Measuring the robustness of predictive probability for early stopping in two-group comparisons

We report physical experiments are often expensive and time-consuming. Test engineers must certify the compatibility of aircraft and their weapon systems before they can be deployed in the field, but the testing required is time consuming, expensive, and resource limited. Adopting Bayesian adaptive designs is a promising way to borrow from the successes seen in the clinical trials domain. The use of predictive probability (PP) to stop testing early and make faster decisions is particularly appealing given the aforementioned constraints. Given the high-consequence nature of the tests performed in the national security space, a strong understanding of new methods is required before being deployed. Although PP has been thoroughly studied for binary data, there is less work with continuous data, where many reliability studies are interested in certifying the specification limits of components. A simulation study evaluating the robustness of this approach indicates early stopping based on PP is reasonably robust to minor assumption violations, especially when only a few interim analyses are conducted. The simulation study also compares PP to conditional power, showing its relative strengths and weaknesses. A post-hoc analysis exploring whether release requirements of a weapon system from an aircraft are within specification with desired reliability resulted in stopping the experiment early and saving 33% of the experimental runs.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Rating of a Pitch Bearing for a 1.5-Megawatt Wind Turbine

Slew ring or "pitch" bearings are used in wind turbines to connect the blade root to the hub. They support the resulting simultaneous radial, axial, and overturning moment loads while allowing relative rotation of the blade with respect to the hub. NREL has recently begun a research program related to pitch bearing reliability, recognizing its growing importance for wind turbines. The purpose of this first paper is to describe the rating analysis for a reference pitch bearing representative of that used a 1.5-megawatt (MW) wind turbine. The analysis will serve as a baseline for future finite-element analyses and strain and deflection measurements of an installed pitch bearing. If successful, this work will enable the design and specification of more reliable pitch bearings, a key concern in the long-term operation of land-based wind turbines and new development of offshore wind turbines.

17 WIND ENERGY↗
DOE OSTI2025

Benchmarking optimization methods for materials research: Gradient descent and Bayesian optimization for lithium-ion battery aging diagnostics

Accurate and efficient parameter estimation is essential for battery diagnostics and aging analysis. Here, in this study, we compare two optimization-based approaches—gradient descent and Bayesian optimization—for extracting parameters from differential voltage analysis in lithium-ion batteries. While these techniques are widely used, their relative strengths and limitations for this application are not well understood. The study evaluates the trade-offs between these methods in terms of result quality, computational cost, and reliability within this specific application. The diagnostic results from our battery data suggest adopting gradient descent as an initial method for rapid and efficient analysis, while employing more stable optimization techniques, such as Bayesian optimization, as a verification step to mitigate potential instability. Comparing the two methods provides information on algorithmic choice, while inspiring further discussions on selecting appropriate techniques for specific research tasks.

Zhao, Ziqing [Boston Univ., MA (United States)] (O↗
DOE OSTI2020

Exploring physics of ferroelectric domain walls via Bayesian analysis of atomically resolved STEM data

The physics of ferroelectric domain walls is explored using the Bayesian inference analysis of atomically resolved STEM data. We demonstrate that domain wall profile shapes are ultimately sensitive to the nature of the order parameter in the material, including the functional form of Ginzburg-Landau-Devonshire expansion, and numerical value of the corresponding parameters. The preexisting materials knowledge naturally folds in the Bayesian framework in the form of prior distributions, with the different order parameters forming competing (or hierarchical) models. Here, we explore the physics of the ferroelectric domain walls in BiFeO 3 using this method, and derive the posterior estimates of relevant parameters. More generally, this inference approach both allows learning materials physics from experimental data with associated uncertainty quantification, and establishing guidelines for instrumental development answering questions on what resolution and information limits are necessary for reliable observation of specific physical mechanisms of interest.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2021

Computational general relativistic force-free electrodynamics: II. Characterization of numerical diffusivity

Scientific codes are an indispensable link between theory and experiment; in (astro-)plasma physics, such numerical tools are one window into the universe’s most extreme flows of energy. The discretization of Maxwell’s equations – needed to make highly magnetized (astro)physical plasma amenable to its numerical modeling – introduces numerical diffusion. It acts as a source of dissipation independent of the system’s physical constituents. Understanding the numerical diffusion of scientific codes is the key to classifying their reliability. It gives specific limits in which the results of numerical experiments are physical. We aim at quantifying and characterizing the numerical diffusion properties of our recently developed numerical tool for the simulation of general relativistic force-free electrodynamics by calibrating and comparing it with other strategies found in the literature. Our code correctly models smooth waves of highly magnetized plasma. We evaluate the limits of general relativistic force-free electrodynamics in the context of current sheets and tearing mode instabilities. We identify that the current parallel to the magnetic field (j ∥ ), in combination with the breakdown of general relativistic force-free electrodynamics across current sheets, impairs the physical modeling of resistive instabilities. We find that at least eight numerical cells per characteristic size of interest (e.g., the wavelength in plasma waves or the transverse width of a current sheet) are needed to find consistency between resistivity of numerical and of physical origins. High-order discretization of the force-free current allows us to provide almost ideal orders of convergence for (smooth) plasma wave dynamics. The physical modeling of resistive layers requires suitable current prescriptions or a sub-grid modeling for the evolution of j ∥ .

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

Development and Applications of an eReaxFF Force Field for Graphitic Anodes of Lithium-Ion Batteries

Graphene is one of the most promising materials for lithium-ion battery anodes due to its superior electronic conductivity, high surface area for lithium intercalation, fast ionic diffusivity and enhanced specific capacity. A reliable description of many battery processes requires an explicit description of electrochemical interactions involving electrons. A detailed atomistic modeling of electronic conduction and non-zero voltage simulations of graphitic materials require the inclusion of an explicit electronic degree of freedom. To enable large length- and time-scale simulations of electron conduction in graphitic anodes, we developed an eReaxFF force field concept describing graphitic materials with an explicit electron. The newly developed force field, verified against quantum chemistry-based data describing, amongst others, electron affinities and equation of states, reproduces the qualitative behavior of electron conductivity in pristine and imperfect graphitic materials at different applied temperatures and voltages. In addition, excess electron localization near a defect site estimated from eReaxFF simulations agree quite well with the corresponding density functional theory calculations. Here, our eReaxFF simulations show the initiation of lithium-metal-plating driven by electron transfer from the graphene surface to the exposed lithium ions demonstrating the method’s potential for studying lithium-graphene interactions with explicit electrons and explain many unresolved electrode and electrode-electrolyte interface processes.

25 ENERGY STORAGE↗
DOE OSTI2022

Near-Term Reliability and Resilience (NTRR) (Final Report)

The Near-Term Reliability and Resiliency (NTRR) was awarded in December 2020 as an inter-lab project to examine the reliability and resilience of the electricity grid and natural gas transportation availability. The project builds on studies conducted by The North American Electric Reliability Corporation (NERC), the U.S. Department of Energy (DOE), and other non-governmental research and operational focused on reliability and resilience analyses challenges. The research was conceived to address near-term scenarios (within 10 years), when many local and regional policy transitions could begin to impact grid reliability, resilience, and supporting infrastructure availability. To integrate the natural gas interdependency, the team began with the generating capacity and demand projections from the 2020 NERC Long-Term Reliability Assessment and the Bulk Electric System (BES) transmission topologies defined in the Western Electricity Coordinating Council (WECC) Anchor Data Set, Eastern Interconnection Reliability Assessment Group Multi-Regional Modeling Working Group (ERAG/MMWG) Data Set, the team calculated baseline regional power sector gas demands from present electricity delivery year through the end of delivery year 2030/31 by applying security constrained economic dispatch. This demand was compiled along with demand projections for regional residential, commercial, and industrial natural gas demands from the most recent Energy Information Administration (EIA) Annual Energy Outlook Reference Case into Deloitte’s MarketBuilder® North American Gas Model. Through the application of these demands, MarketBuilder® was projected the topology of natural gas flows in the natural gas pipeline network across the interconnected North American system along with regional natural gas prices that may be seen by market participants in future years Additionally, contingencies and sensitivities focused on the built models of the Eastern Interconnection (EI) and Western Interconnection (WI). They address challenges from the following with the outcomes being an identification of performance under the extreme conditions and an identification of potential grid weaknesses that should be addressed to mitigate the reduced performance and improve the resilience and reliability of the specific regions as well as the National Grid: • Weather events including extreme heat, extreme cold, high wind, no wind, wind and solar forecasting errors, and wildfires. • Gas availability, factoring in supply disruption (contractual and physical), seasonal availability constraints, and infrastructure limitations; and • Transmission availability and congestion.

03 NATURAL GAS↗
DOE OSTI2025

Long-Duration Energy Storage Grid Integration-Valuation Framework and Incentive Gaps

Given these challenges and current modeling gaps on Long Duration Energy Storage (LDES), enhancing the structure and design of existing planning, operations, and organized wholesale markets can better characterize the value of LDES to the power system. To more thoroughly assess the gaps and barriers to LDES investment and readiness for integration into a future grid, we conducted stakeholder outreach through an online survey, interviews with individual independent system operators/regional transmission organizations, and a literature review. Based on this assessment, we identified a set of opportunities for LDES focused development, including a framework to quantify the contributions of LDES on resource adequacy, reliability, and resiliency. Specifically, we identify the potential demand for and benefits of an open-source, LDES-centric evaluation framework that can guide future planning, operations, market design, and policy reforms.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2026

Solar Radiation Research Laboratory (SRRL) Core Project Final Report: Fiscal Years 2022-2024

The Solar Radiation Research Laboratory (SRRL) at the National Laboratory of the Rockies (NLR) is a world-leading solar calibration and measurement facility and maintains and disseminates the World Radiation Reference (essentially the W/m2) for the United States that is essential for traceable and accurate measurements of solar radiation at all solar generation facilities. SRRL operates two calibration facilities that meet International Standards Organization-17025 (ISO-17025) standards and provide unique high-quality calibrations to NREL and other U.S. Department of Energy laboratories. The Baseline Measurement System (BMS) at SRRL provides a high-quality record of solar irradiance and surface meteorological conditions. SRRL capabilities are used to develop (1) improved methods for the calibration of solar radiometers; (2) new standards through the ISO, the International Electrotechnical Commission (IEC), and the American Standards for Testing of Materials (ASTM) International; (c) solar radiation and meteorological models; and (d) advanced instrumentation and methods for operating solar measurement stations. The SRRL datasets are also critical for the validation of new models and datasets, such as the National Solar Radiation Database (NSRDB). The research and development of solar radiation measurement systems and resource modeling techniques are essential for advancing the scientific basis for producing reliable resource data. Specifically, the spatial, temporal, and spectral (wavelength dependency) characteristics of the solar resource are required in several different time frames for various project phases.

14 SOLAR ENERGY↗
DOE OSTI2022

An Enhanced Computational Framework for Energy Storage Participation in Transmission Planning with Electricity Market Participation: Dynamic Market Participation Restriction Estimation

In the previous study and report, we developed a computational framework to explore the technical and economic viability of the dual use of pumped storage hydropower (PSH) for both transmission assets and market participation. The rationale for the dual-use application is to improve the resource utilization rate and reduce the cost recovery burden. A PSH-based transmission solution generally has a large capacity, which corresponds to a higher investment cost compared to a traditional line solution. Market participation may allow the PSH asset to offset part of its high investment cost. A critical question is whether it is economically and technically viable to allow dual use of a PSH-based transmission project without jeopardizing transmission system reliability. And a more specific follow-up question is how to improve market participation performance while maintaining transmission reliability. In this study, we extend the computational framework by updating the method to determine transmission service obligation requirements dynamically based on the possibility of the need for transmission service in operation. Specifically, we correlate the need for transmission service with the probability of thermal overloading on a monitored transmission line, which is essentially based on the probability distribution of power flow and its probability of exceeding the line rating based on system dispatch and operational uncertainties. In addition, the need depends on the level of risk that a system operator is willing to take. The higher the risk tolerance, the lower the requirement that the system operator would apply to the PSH project as a transmission asset. The requirements are updated every day before the PSH project determines its market participation strategy. With the updated transmission service requirements, it is expected that a PSH project can serve as a transmission asset when the transmission system is at risk and really needs it, while it can participate in a market with sufficient information and certain restrictions. In this way, the transmission service quality and market participation performance can both be improved.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗